Effects of carbon taxes on different industries by fuzzy goal programming: A case study of the petrochemical-related industries, Taiwan

Implementation of a carbon tax is one of the major ways to mitigate CO₂ emission. However, blanket taxes applied to all industries in a country might not always be fair or successful in CO₂ reduction. This study aims to evaluate the effects of carbon taxes on different industries, and meanwhile to find an optimal carbon tax scenario for Taiwan's petrochemical industry. A fuzzy goal programming approach, integrated with gray prediction and input-output theory, is used to construct a model for simulating the CO₂ reduction capacities and economic impacts of three different tax scenarios. Results indicate that the up-stream industries show improved CO₂ reduction while the down-stream industries fail to achieve their reduction targets. Moreover, under the same reduction target (i.e. return the CO₂ emission amount to year 2000 level by 2020), scenario SWE induces less impact than FIN and EU on industrial GDP. This work provides a valuable approach for researches on model construction and CO₂ reduction, since it applies the gray envelop prediction to determine the boundary values of the fuzzy goal programming model, and furthermore it can take the economic interaction among industries into consideration.